Method for Forming Database on Basis of Relationship Between Video Data, and Database Formation System

ABSTRACT

The present invention relates to a method and system for constructing a database (DB) based on mutual relations between pieces of video data. The present invention provides the method of constructing a DB based on mutual relations between pieces of video data, including 1) generating one or more nodes so that pieces of identical video data are included in an identical node, 2) generating pieces of node information about respective generated nodes, 3) comparing comparison target video data with pieces of video data of the respective nodes, and then setting relations between the comparison target video data and the pieces of video data of the respective nodes, and 4) updating pieces of node information about the respective nodes, based on the set relations, and also provides a DB construction system using the method.

TECHNICAL FIELD

The present invention relates, in general, to a method and system forconstructing a database (DB) and, more particularly, to a method andsystem for constructing a DB which makes it possible to compare piecesof video data with each other, set mutual relations for identicalnessbetween the pieces of video data, and determine efficiently the mutualrelations between the pieces of video data based on the set mutualrelations for identicalness.

BACKGROUND ART

With the development of Internet technology, a great amount of data ispresent on the Internet. In particular, recently, cases where video datais uploaded or downloaded, or where video data is provided in real timeusing a streaming service have greatly increased. Further, video dataservices gradually occupy a larger part of even web services, such asvarious types of search portal websites, blogs, cafes, ormini-homepages. Furthermore, there are many cases where pieces of videodata, such as video data related to broadcasts or movies, are providedover the Internet.

In particular, cases where original video data is edited or adapted by aplurality of users and is provided in a modified form on the web havealso increased. Further, for example, a plurality of episodes appear asseparate video data within a single drama series, and a piece of videodata of one hour or longer in which a plurality of short music videosare compiled may be present. Furthermore, a case where part of aspecific drama is included in video data edited by a user as a part ofthe video data may exist. If relations between pieces of video data,which are present to be modified or edited in various forms as above,can be detected, identical or similar pieces of video data present invarious forms on the network may be conveniently searched for. Further,the copyrights management of the video data may also be convenientlyperformed. Furthermore, if mutual relations between pieces of video datathat are present in various forms on the web, but have a predeterminedcommon relation can be detected, it is possible to utilize the videodata as advertisement data or as other pieces of additional data basedon the mutual relations. However, a conventional video DB is limited inthat it simply stores only information about individual pieces of videodata without reflecting such mutual relations.

DISCLOSURE Technical Problem

Accordingly, the present invention has been made keeping in mind theabove limitations, and an object of the present invention is to providea method and system that are capable of constructing a video database(DB) based on mutual relations between pieces of video data.

Another object of the present invention is to provide a method andsystem that are capable of constructing a video ontology DB by definingmutual relations between pieces of video data so that the video DB canbe constructed based on the mutual relations between the pieces of videodata.

A further object of the present invention is to provide a method andsystem that construct a video DB based on mutual relations betweenpieces of video data, thus conveniently and efficiently classifying anddetermining mutual relations between a large number of pieces of videodata scattered on the web depending on the types of relations, and alsoclassifying the type of information which specific video data has fromthe statistical characteristics of the relations.

Yet another object of the present invention is to construct a video DBbased on mutual relations between pieces of video data, thus efficientlyproviding various types of supplementary services, such as video datasearching, rights management, and advertising services, for example,viral marketing.

Technical Solution

In order to accomplish the above objects, the present invention providesa method of constructing a database (DB) based on mutual relationsbetween pieces of video data, including 1) generating one or more nodesso that pieces of identical video data are included in an identicalnode; 2) generating pieces of node information about respectivegenerated nodes; 3) comparing comparison target video data with piecesof video data of the respective nodes, and then setting relationsbetween the comparison target video data and the pieces of video data ofthe respective nodes; and 4) updating pieces of node information aboutthe respective nodes, based on the set relations.

In this case, the node information at 2) may include node identifierinformation uniquely assigned to each node.

Further, the node information at 2) may include information about aphysical location at which the video data is located.

Furthermore, each relation between the comparison target video data andthe pieces of video data set at 3) may correspond to at least one of acase where the comparison target video data is different from all of thepieces of video data of the respective nodes, a case where thecomparison target video data is completely identical to one of thepieces of video data of the respective nodes, and a case where thecomparison target video data partially overlaps at least one of thepieces of video data of the respective nodes.

Furthermore, if the relation is set as the case where the comparisontarget video data is different from all of the pieces of video data ofthe respective nodes, 4) may be configured such that a new node isgenerated, the comparison target video data is included in the new node,and node information about the new node is generated.

Furthermore, if the relation is set as the case where the comparisontarget video data is completely identical to one of the pieces of videodata of the respective nodes, 4) may be configured such that thecomparison target video data is included in a node including thecompletely identical video data, and node information about the node isupdated.

Furthermore, the case where the comparison target video data partiallyoverlaps at least one of the pieces of video data of the respectivenodes may be one of a case where the comparison target video dataincludes at least one of the pieces of video data of the respectivenodes, a case where the comparison target video data is included in atleast one of the pieces of video data of the respective nodes, a casewhere a part of the comparison target video data completely overlaps atleast one of the pieces of video data of the respective nodes, and acase where a part of the comparison target video data incompletelyoverlaps at least one of the pieces of video data of the respectivenodes.

Furthermore, 4) may include 4-1) determining to which one of theoverlapping cases a current case corresponds; 4-2) generating a newnode; 4-3) updating node information about the overlapping nodes incorrespondence with each overlapping case; and 4-4) updating nodeinformation about the new node in correspondence with each overlappingcase.

Further, 4-3) and 4-4) may be configured to generate information abouteach overlapping case as edge information indicating a connectingrelationship between the new node and the overlapping nodes, and updatethe edge information so that the edge information is included in thenode information.

In accordance with another aspect of the present invention, there isprovided a system for constructing a database (DB) based on mutualrelations between pieces of video data, including a comparison unit forcomparing comparison target video data with pieces of video data storedin a DB, and setting mutual relations between the pieces of video data;a DB management unit for generating one or more nodes and pieces of nodeinformation so that pieces of identical video data are included in anidentical node, and managing pieces of node information about respectivenodes based on mutual relations set by the comparison unit comparing thecomparison target video data with the pieces of video data stored in theDB; and the DB for storing the nodes and the node information generatedby the DB management unit, and storing the pieces of video data incorrespondence with respective nodes, based on related data generatedand updated by the DB management unit depending on the mutual relationsset by the comparison unit.

Further, the comparison unit may compare the comparison target videodata with the pieces of video data of the nodes stored in the DB, andset each mutual relation as at least one of a case where the comparisontarget video data is different from all of the pieces of video data ofthe respective nodes, a case where the comparison target video data iscompletely identical to one of the pieces of video data of therespective nodes, and a case where the comparison target video datapartially overlaps at least one of the pieces of video data of therespective nodes.

Furthermore, if the mutual relation is set as the case where thecomparison target video data is different from all of the pieces ofvideo data of the respective nodes, the DB management unit may beconfigured such that a new node is generated, the comparison targetvideo data is included in the new node, and node information about thenew node is generated.

Furthermore, if the mutual relation is set as the case where thecomparison target video data is completely identical to one of thepieces of video data of the respective nodes, the DB management unit maybe configured such that the comparison target video data is included ina node including the completely identical video data, and nodeinformation about the node is updated.

Furthermore, the case where the comparison target video data partiallyoverlaps at least one of the pieces of video data of the respectivenodes may be one of a case where the comparison target video dataincludes at least one of the pieces of video data of the respectivenodes, a case where the comparison target video data is included in atleast one of the pieces of video data of the respective nodes, a casewhere a part of the comparison target video data completely overlaps atleast one of the pieces of video data of the respective nodes, and acase where a part of the comparison target video data incompletelyoverlaps at least one of the pieces of video data of the respectivenodes.

Furthermore, the DB management unit may determine to which one of theoverlapping cases a current case corresponds, generates a new node,update node information about the overlapping nodes in correspondencewith each overlapping case, and update node information about the newnode in correspondence with each overlapping case.

Advantageous Effects

According to the present invention, there can be provided a method andsystem that are capable of constructing a video DB based on mutualrelations between pieces of video data.

Further, according to the present invention, there can be provided amethod and system that are capable of constructing a video ontology DBby defining mutual relations between pieces of video data so that thevideo DB can be constructed based on the mutual relations between thepieces of video data.

Furthermore, according to the present invention, there is an advantagein that a method and system can be provided which construct a video DBbased on mutual relations between pieces of video data, thusconveniently and efficiently classifying and determining mutualrelations between a large number of pieces of video data scattered onthe web depending on the types of relations, and also classifying thetype of information which specific video data has from the statisticalcharacteristics of the relations.

Furthermore, the present invention is advantageous in that it constructsa video DB based on mutual relations between pieces of video data, thusefficiently providing various types of supplementary services, such asvideo data searching, rights management, and advertising services, forexample, viral marketing.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram showing the configuration of an embodiment forperforming a method of constructing a DB based on mutual relationsbetween pieces of video data according to the present invention;

FIG. 2 is a flowchart showing an embodiment of a method of constructinga DB based on mutual relations between pieces of video data according tothe present invention;

FIGS. 3 and 4 are diagrams showing examples of nodes and nodeinformation generated at steps S100 and S110;

FIG. 5 is a diagram showing mutual relations between pieces of videodata to be compared;

FIGS. 6 to 8 are diagrams showing examples of nodes and nodeinformation;

FIGS. 9 and 10 are diagrams showing examples of node information;

FIG. 11 is a diagram illustrating only edge information of nodeinformation for the node IDs of a video DB;

FIG. 12 is a diagram showing mutual relations between nodes in the formof a graph;

FIG. 13 is a diagram showing an embodiment of a method of searching thevideo DB constructed according to the present invention for video data;and

FIGS. 14 to 17 are diagrams illustrating nodes having severalcharacteristic shapes that may appear when video data is generatedaccording to the present invention.

BEST MODE

Hereinafter, embodiments of the present invention will be described indetail with reference to the attached drawings.

FIG. 1 is a diagram showing the configuration of an embodiment of asystem for performing a method of constructing a database (DB) based onmutual relations between pieces of video data according to the presentinvention and schematically illustrating the overall concept of thepresent invention.

Referring to FIG. 1, the overall concept of the present invention willbe described in brief below. Referring to FIG. 1, a system 100 forperforming a method of constructing a DB based on mutual relationsbetween pieces of video data according to the present embodiment(hereinafter simply referred to as a “DB construction system”) includesa comparison unit 10, a DB management unit 20, and a database (DB) 30.

The comparison unit 10 functions to compare comparison target video datawith pieces of video data stored in the DB 30, and set mutual relationsbetween the comparison target video data and the stored video data.Here, the term “mutual relation” denotes a relation corresponding to oneof difference, complete identicalness, and overlapping between pieces ofvideo data to be compared with each other.

The DB management unit 20 performs a management function, such as thegeneration and updating of various types of related data so that piecesof video data can be stored in the DB 30 in correspondence with themutual relations set by the comparison unit 10 depending on the mutualrelations.

The DB 30 functions to store the pieces of video data in correspondencewith the mutual relations set by the comparison unit 10 using the piecesof related data generated and updated by the DB management unit 20depending on the mutual relations. The DB 30 may include and store alltypes of data required to implement the method of the present invention.

The operation of the DB construction system 100 having the aboveconfiguration will be described in brief below.

First, in the DB 30, one or more nodes are generated so that pieces ofidentical video data are included in the same node, and pieces of nodeinformation about respective generated nodes are generated. Here, theterm “identical” means that pieces of information are completelyidentical, that is, means that the entirety of a piece of video datafrom beginning to end is completely identical to that of another pieceof video data. In other words, a single node is composed of only piecesof identical video data.

In this state, when comparison target video data (target data to beclassified in the DB) is input, the comparison target video data iscompared with pieces of video data of respective nodes, and relationsbetween the comparison target video data and the pieces of video data ofthe respective nodes are set. Here, the term “relation” means at leastone relation of “difference”, “complete identicalness”, and“overlapping”, as described above.

If the relations have been set, pieces of node information about therespective nodes are updated based on the set relations. This “updating”means that related node information in the DB is revised in such a wayas to generate a new node based on each relation (in the case ofdifference and overlapping), or to include video data in an existingnode (in the case of complete identicalness), and to store and updateinformation corresponding to the relation in each piece of nodeinformation.

Next, a method of constructing a DB based on mutual relations betweenpieces of video data, which is performed under the configuration of FIG.1, will be described in detail with reference to drawings from FIG. 2.

FIG. 2 is a flowchart showing an embodiment of a method of constructinga DB based on mutual relations between pieces of video data according tothe present invention.

Referring to FIG. 2, the DB construction system 100 generates one ormore nodes so that pieces of identical video data are included in thesame node (S100), and pieces of node information about respectivegenerated nodes are generated (S110).

FIGS. 3 and 4 are diagrams showing examples of nodes and nodeinformation generated at steps S100 and S110. Referring to FIG. 3, itcan be seen that three nodes A, B, and C are generated, and pieces ofnode information are generated for respective nodes. It is assumed thateach node is configured to include only pieces of completely identicalvideo data when it is generated in an initial state. Also, it is assumedthat video data included in same node are distinguishable with videodata included in other nodes, that is, overlapping portions are notpresent between video data in a node and video data in other node.

For example, in a case where video data having the file name “abc.avi”is present in location information “www.abc.com/abc” and video datahaving the file name “def.avi” is present in location information“www.def.com/def” on Internet websites, if the two pieces of video dataare completely identical from beginning to end despite the file namesthereof being different from each other, the pieces of video data areregarded as identical video data, and may be included in the same node(for example, node A of FIG. 4). In this case, as shown in FIG. 4, avideo data field is required to store video data itself, wherein twopieces of video data are identical to each other, so that it issufficient to store only one of the two pieces of video data, andrespective pieces of physical address information (locationinformation), that is, “www.abc.com/abc” and “www.def.com/def,” can bestored as node information in the location information.

In this way, nodes are generated so that pieces of non-overlapping videodata, that is, distinguishable video data, belong to different nodes andpieces of identical video data belong to a single same node, and so thatnode information can be generated for each node, as illustrated in FIG.4.

The node information of FIG. 4 may include a node Identifier (ID) fieldthat is the unique identifier of each node, a video data field forstoring video data itself, as described above, and a locationinformation field for representing information about a physical locationat which each piece of video data is present on the web. Here, it isapparent that video data is separately stored in the DB 30 without beingstored in the video data field, and that the video data field stores theinternal location information of the DB 30. Further, the nodeinformation may include an edge information field, wherein edgeinformation is required to store information indicative of mutualrelations with other nodes depending on the mutual relations, which willbe described later. At the above-described steps S100 and S110, thenodes are each composed of different pieces of video data and there isno relation therebetween, so that the edge information field is in anempty state, and the corresponding relations are recorded laterdepending on mutual relations with other pieces of video data. Thisoperation will be described in detail below. Further, it is apparentthat node information may also be configured to store other additionalinformation, such as the size of data, time information, copyrightsinformation or metadata information, in addition to the informationshown in FIG. 4.

Referring back to FIG. 2, in a state in which nodes and node informationare generated at steps S100 and S110, if comparison target video data isinput, the comparison target video data is compared with the pieces ofvideo data in respective nodes (S 120), and mutual relations between thecomparison target video data and the pieces of video data of therespective nodes are set (S 130).

Here, the term “comparison target video data” denotes target video datato be newly added to the video DB. Methods for comparing such comparisontarget video data with the pieces of video data of the respective nodescan be implemented using conventional well-known video data comparisonmethods. Methods of determining whether pieces of video data areidentical to each other by comparing the piece of video data may beimplemented using, for example, methods of extracting fingerprints andcomparing the fingerprints with each other, as well known in the priorart. The use of fingerprints can be implemented using audio fingerprintsand/or video fingerprints. However, since the present invention must setmutual relations at step S130, it must be able to determine all mutualrelations including a relation in which pieces of video data partiallyoverlap each other, without being limited to the simple determination ofwhether pieces of video data are identical, based on a comparisonbetween the pieces of video data. Therefore, at step S120, it ispreferable to use a comparison method capable of determining evenwhether pieces of video data to be compared are completely identical orcompletely different from each other, or whether the pieces of videodata partially overlap each other. Further, since the cases where piecesof video data partially overlap each other include a case where onepiece of video data includes or is included in the other piece of videodata, and a case where parts of the pieces of video data completely orincompletely overlap each other, comparison methods capable ofdetermining relations even in cases such as those must be used.

As examples of such a comparison method, there can be used comparisonmethods filed by the present applicant and disclosed in Korean PatentApplication No. 10-2007-0044251 (entitled “Method and apparatus forgenerating audio fingerprint data and method and apparatus for comparingaudio data using the same”), Korean Patent Application No.10-2007-0054601 (entitled “Method and apparatus for determiningidenticalness of video data and detecting an identical section”), KoreanPatent Application No. 10-2007-0060978 (entitled “Method and system forclustering pieces of video data having identicalness among pieces ofvideo data”), and Korean Patent Application No. 10-2007-0071633(entitled “Method and apparatus for providing a video data searchservice using video data clusters”).

In accordance with technologies disclosed in the patent applicationfiled by the present applicant, it may be determined not only whetherpieces of video data to be compared have identicalness, but also whetherpieces of video data are partially identical, that is, whether theypartially overlap each other, as well as whether they are completelyidentical, by exactly detecting which section is identical, whichsection is non-identical, etc., with respect to individual sections. Inaddition, information about a section in which the pieces of video dataoverlap each other may also be exactly detected.

By using the comparison technologies disclosed by the present applicant,the pieces of video data are compared, and mutual relations between thepieces of video data that are compared may be set by exactly determiningthe mutual relations, that is, relations indicating whether the piecesof video data are completely identical, are different from each other,or partially overlap each other, at steps S120 and S130. When theabove-described comparison technologies of the present applicant areused, the node information of FIG. 4 may include fingerprint informationused in comparison. Of course, in addition to the fingerprintinformation, any type of information used in comparison, for example,feature data indicating the features of the corresponding video data,for example, DNA information, may be included in the node information.

The present invention is not intended to provide a method itself ofcomparing pieces of video data, and such a comparison method can beimplemented using any type of conventional technology, in addition tothe technologies disclosed in the patents filed by the presentapplicant, as long as the conventional technology can clearlydiscriminate the above-described mutual relations from one another, andthus an additional detailed description thereof will be omitted.

FIG. 5 is a diagram showing mutual relations between pieces of videodata to be compared, as described above.

Referring to FIG. 5, relations denote mutual relations when pieces ofvideo data are compared with each other, wherein six cases, including(a) difference, (b) complete identicalness, (c) including, (d) beingincluded, (e) partially complete overlapping, and (f) partiallyincomplete overlapping, are illustrated. Among the relations, (c) to (f)belong to partially overlapping forms.

Referring back to FIG. 2, when the mutual relation between thecomparison target data and the piece of video data of each node, whichcorresponds to one of the relations shown in FIG. 5, is set at stepsS120 and S130, the node information about each node is updated based onthe set mutual relation (S 140).

The updating of the node information may be performed depending on theindividual cases of FIG. 5 as follows.

First, if the mutual relation is set as a case where the comparisontarget video data is different from all pieces of video data of therespective nodes ((a) of FIG. 5), the comparison target video data is anew video data having no relation with any previously generated nodes,so that a new node is generated, the comparison target video data isincluded in the generated new node, and then node information about thenew node is generated. This is performed in a manner similar to that ofsteps S100 and S110 of FIG. 2. In this case, the new node, that is, thenode including the comparison target video data, is not related toexisting nodes, and thus edge information (see FIG. 4) indicating mutualrelations with other nodes does not need to be especially added orupdated. In this form, the existing nodes and the newly generated newnode (node D) are shown in FIG. 6. As shown in FIG. 6, there is noconnection (edge information) between the existing nodes and the newnode.

Next, if the mutual relation is set as a case where the comparisontarget video data is completely identical to one of pieces of video dataof respective nodes ((b) of FIG. 5), the comparison target video data isincluded in a node including the completely identical video data, andnode information about the node is updated. For example, in a state inwhich nodes are generated, as shown in FIG. 2, if the comparison targetvideo data is completely identical to the video data of existing node A,the comparison target video data must be merged into node A, so thatnode information about node A is updated. In this case, the updated nodeinformation may be only location information (see FIG. 2) that is added.Even in this case, since relations with other nodes are not changed,there is no need to update edge information, as described above in thecase of the relation of difference. This case is shown in FIG. 7.

Next, in a case where the comparison target video data partiallyoverlaps at least one of the pieces of video data of the respectivenodes ((c), (d), (e), and (f) of FIG. 5), how the pieces of video dataoverlap each other, that is, an overlapping shape among shapes in (c),(d), (e), and (f) of FIG. 5, is firstly set, a new node is generated,the comparison target video data is included in the generated new node,and node information about the new node is recorded. This procedure issame to that of the above-described case of the relation of difference.

Next, pieces of node information about all existing nodes having therelation of partially overlapping with the comparison target video dataare updated in correspondence with the respective overlapping cases((c), (d), (e), and (f) of FIG. 5), and node information about thegenerated new node is updated in correspondence with each overlappingcase. For example, as shown in FIG. 8, when a new node is node E, andthere is a relation in which the video data of node E includes the videodata of node A, information indicating that node A is included in node Eis first recorded in an edge information field (see FIG. 4) included inthe node information of node A. In this case, the updated edgeinformation and node information about node A can be indicated, as shownin FIG. 9. Then, node information about node E is updated, and thisupdating can be performed by recording information indicating that nodeE includes node A. In this case, the updated edge information and nodeinformation about node E can be indicated, as shown in FIG. 10.

When such a procedure is performed on pieces of comparison target videodata that are newly input, a video DB in which relations among allpieces of video data can be determined depending on mutual relations forrespective nodes can be constructed. FIG. 11 illustrates only edgeinformation of node information for each node ID of the video DBconstructed through the above procedure. Referring to FIG. 11, it can beseen that, as represented in edge information for each node, nodes A toE have mutual relations, such as including, partially completeoverlapping, partially incomplete overlapping, or being included, asedge information based on mutual relations with other nodes. When suchinformation is represented as a graph, it can be seen as shown in FIG.12. By this graph, mutual relations between the nodes may beconveniently determined, and other nodes having interrelations with anyone node may be efficiently searched for using the information shown inFIGS. 11 and 12.

FIG. 13 is a diagram showing an embodiment of a method of searching thevideo DB, constructed as described above, for video data.

Referring to FIG. 13, nodes ranging from A to O are generated, andmutual relations between the nodes are shown. Nodes represented in avertical relationship in FIG. 13 indicate a relation in which a node atan upper level include nodes at a lower level (a relation in which thenodes at the lower level are included in the node at the upper level),and nodes in the same horizontal line have a relation in which they aredifferent from each other or partially overlap each other. In FIG. 13,node A, for example, includes nodes B, F, G, and H, node B includesnodes I, J, and K and has the relation of partially incompletelyoverlapping with node D (see FIG. 5), and node C includes nodes K, L,and M and has the relation of partially completely overlapping with nodeD (see FIG. 5). Further, it can be seen that node D has the relation ofpartially completely overlapping with node E, and node E includes nodesN and O.

In this state, a procedure for obtaining a set of nodes connected via amaximum of n intermediate nodes based on node B is described as follows.First, node IDs of nodes (nodes A, D, I, J, and K) directly connected tonode B are checked by referring to edge information included in nodeinformation about node B. Next, node IDs of nodes (nodes F, G, H, C, andE) directly connected to the directly connected nodes are obtained byreferring to the edge information of the node information of the checkednode IDs. When this procedure is repeated n times, a set of nodesconnected via a maximum of n intermediate nodes based on node B can beobtained. Mutual relations with other nodes based on node B may beefficiently determined using the obtained nodes. These mutual relationsmay be arranged into a separate DB so that they can be efficiently usedto search for video data itself or perform advertising, marketing andtracking.

FIGS. 14 to 17 are diagrams illustrating several characteristic shapesthat may appear when the video DB is constructed according to thepresent invention. Rectangles in the drawings denote nodes, and arrowsdenote edges.

FIG. 14 is a diagram showing a case where a single node includes aplurality of other nodes and the other nodes have little relationshiptherebetween. The case of FIG. 14 shows a shape frequently appearing ina broadcast program divided into a plurality of independent sections.

FIG. 15 illustrates a case where a single node is included in aplurality of other nodes, and the other nodes has little relationshiptherebetween. The case of FIG. 15 shows a shape frequently appearing inpictures, such as an animated feature or a drama including the sameopening/ending scenes.

FIG. 16 illustrates a case where a plurality of nodes are included in asingle node, but very complicated relations are formed between theplurality of nodes in secondary searching. The case of FIG. 16 shows ashape frequently appearing in famous video data in which a plurality ofedited highlights having different lengths or video qualities arepresent. FIG. 16 shows that “Paparazzi” which is a music video of asinger named “Lady Gaga” is arranged into a video DB, wherein theleftmost node is an original music video, and nodes in right sidescorrespond to edited versions of the original music video.

FIG. 17 illustrates a case where ‘including’ relations are gathered inseveral terminal nodes via a complicated relation from a plurality ofindependent nodes through intermediate nodes, and shows a shape mainlyappearing in a long series video product having many repetitions. In theshape of FIG. 17, highlights or good scenes frequently appearing overseveral installments are located in the terminal nodes, and most uppernodes denote adjacent episodes of the series. FIG. 17 illustrates anexample of an animated feature named “One Piece.”

The shapes of FIGS. 14 to 17 are exemplarily shown for the convenienceof description, but, in practice, shapes may appear in a morecomplicated form than those of the drawings.

In the above description, although preferred embodiments of the presentinvention have been described with reference to the detailed descriptionand drawings, the present invention is not limited by those embodiments,and those skilled in the art to which the present invention pertainswill appreciate that various modifications and other equivalentembodiments are possible from the above embodiments. Accordingly, itshould be noted that the scope of the present invention should bedefined by the technical spirit of the accompanying claims.

What is claimed is:
 1. A method of constructing a database (DB) based onmutual relations between pieces of video data, comprising: 1) generatingone or more nodes so that pieces of identical video data are included inan identical node; 2) generating pieces of node information aboutrespective generated nodes; 3) comparing comparison target video datawith pieces of video data of the respective nodes, and then settingrelations between the comparison target video data and the pieces ofvideo data of the respective nodes; and 4) updating pieces of nodeinformation about the respective nodes, based on the set relations. 2.The method of claim 1, wherein the node information at 2) includes nodeidentifier information uniquely assigned to each node.
 3. The method ofclaim 1, wherein the node information at 2) includes information about aphysical location at which the video data is located.
 4. The method ofclaim 1, wherein each relation between the comparison target video dataand the pieces of video data set at 3) corresponds to at least one of acase where the comparison target video data is different from all of thepieces of video data of the respective nodes, a case where thecomparison target video data is completely identical to one of thepieces of video data of the respective nodes, and a case where thecomparison target video data partially overlaps at least one of thepieces of video data of the respective nodes.
 5. The method of claim 4,wherein if the relation is set as the case where the comparison targetvideo data is different from all of the pieces of video data of therespective nodes, 4) is configured such that a new node is generated,the comparison target video data is included in the new node, and nodeinformation about the new node is generated.
 6. The method of claim 4,wherein if the relation is set as the case where the comparison targetvideo data is completely identical to one of the pieces of video data ofthe respective nodes, 4) is configured such that the comparison targetvideo data is included in a node including the completely identicalvideo data, and node information about the node is updated.
 7. Themethod of claim 4, wherein the case where the comparison target videodata partially overlaps at least one of the pieces of video data of therespective nodes is one of a case where the comparison target video dataincludes at least one of the pieces of video data of the respectivenodes, a case where the comparison target video data is included in atleast one of the pieces of video data of the respective nodes, a casewhere a part of the comparison target video data completely overlaps atleast one of the pieces of video data of the respective nodes, and acase where a part of the comparison target video data incompletelyoverlaps at least one of the pieces of video data of the respectivenodes.
 8. The method of claim 7, wherein 4) comprises: 4-1) determiningto which one of the overlapping cases a current case corresponds; 4-2)generating a new node; 4-3) updating node information about theoverlapping nodes in correspondence with each overlapping case; and 4-4)updating node information about the new node in correspondence with eachoverlapping case.
 9. The method of claim 8, wherein 4-3) and 4-4) areconfigured to generate information about each overlapping case as edgeinformation indicating a connecting relationship between the new nodeand the overlapping nodes, and update the edge information so that theedge information is included in the node information.
 10. A system forconstructing a database (DB) based on mutual relations between pieces ofvideo data, comprising: a comparison unit for comparing comparisontarget video data with pieces of video data stored in a DB, and settingmutual relations between the pieces of video data; a DB management unitfor generating one or more nodes and pieces of node information so thatpieces of identical video data are included in an identical node, andmanaging pieces of node information about respective nodes based onmutual relations set by the comparison unit comparing the comparisontarget video data with the pieces of video data stored in the DB; andthe DB for storing the nodes and the node information generated by theDB management unit, and storing the pieces of video data incorrespondence with respective nodes, based on related data generatedand updated by the DB management unit depending on the mutual relationsset by the comparison unit.
 11. The system of claim 10, wherein thecomparison unit compares the comparison target video data with thepieces of video data of the nodes stored in the DB, and sets each mutualrelation as at least one of a case where the comparison target videodata is different from all of the pieces of video data of the respectivenodes, a case where the comparison target video data is completelyidentical to one of the pieces of video data of the respective nodes,and a case where the comparison target video data partially overlaps atleast one of the pieces of video data of the respective nodes.
 12. Thesystem of claim 11, wherein if the mutual relation is set as the casewhere the comparison target video data is different from all of thepieces of video data of the respective nodes, the DB management unit isconfigured such that a new node is generated, the comparison targetvideo data is included in the new node, and node information about thenew node is generated.
 13. The system of claim 11, wherein if the mutualrelation is set as the case where the comparison target video data iscompletely identical to one of the pieces of video data of therespective nodes, the DB management unit is configured such that thecomparison target video data is included in a node including thecompletely identical video data, and node information about the node isupdated.
 14. The system of claim 11, wherein the case where thecomparison target video data partially overlaps at least one of thepieces of video data of the respective nodes is one of a case where thecomparison target video data includes at least one of the pieces ofvideo data of the respective nodes, a case where the comparison targetvideo data is included in at least one of the pieces of video data ofthe respective nodes, a case where a part of the comparison target videodata completely overlaps at least one of the pieces of video data of therespective nodes, and a case where a part of the comparison target videodata incompletely overlaps at least one of the pieces of video data ofthe respective nodes.
 15. The system of claim 14, wherein the DBmanagement unit determines to which one of the overlapping cases acurrent case corresponds, generates a new node, updates node informationabout the overlapping nodes in correspondence with each overlappingcase, and updates node information about the new node in correspondencewith each overlapping case.